buildmodel fails on Convolution2D filter_size vs input_size?

[no-zzz-un]

buildmodel fails because the filter_size mismatches the input_size.
i don't understand why input_size is reported as (4,80) when clearly (4,80,80) is passed as input_shape..

i'm using keras version 1.1.0

any ideas?

Using TensorFlow backend.
Now we build the model
(4, 80, 80)
Traceback (most recent call last):
  File "qlearn.py", line 199, in <module>
    main()
  File "qlearn.py", line 196, in main
    playGame(args)
  File "qlearn.py", line 189, in playGame
    model = buildmodel()
  File "qlearn.py", line 45, in buildmodel
    model.add(Convolution2D(32, 8, 8, subsample=(4,4),init=lambda shape, name: normal(shape, scale=0.01, name=name), border_mode='same',input_shape=(img_channels,img_rows,img_cols)))
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/models.py", line 276, in add
    layer.create_input_layer(batch_input_shape, input_dtype)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/engine/topology.py", line 370, in create_input_layer
    self(x)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/engine/topology.py", line 514, in __call__
    self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/engine/topology.py", line 572, in add_inbound_node
    Node.create_node(self, inbound_layers, node_indices, tensor_indices)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/engine/topology.py", line 149, in create_node
    output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/layers/convolutional.py", line 466, in call
    filter_shape=self.W_shape)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 1579, in conv2d
    x = tf.nn.conv2d(x, kernel, strides, padding=padding)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 394, in conv2d
    data_format=data_format, name=name)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 703, in apply_op
    op_def=op_def)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2319, in create_op
    set_shapes_for_outputs(ret)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1711, in set_shapes_for_outputs
    shapes = shape_func(op)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 246, in conv2d_shape
    padding)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 184, in get2d_conv_output_size
    (row_stride, col_stride), padding_type)
  File "/Users/noun/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 149, in get_conv_output_size
    "Filter: %r Input: %r" % (filter_size, input_size))
ValueError: Filter must not be larger than the input: Filter: (8, 8) Input: (4, 80)

[no-zzz-un]

nevermind, just figured out the dim_ordering mismatch